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Object segmentation in images using EEG signals
Mohedano, Eva; Healy, Graham; McGuinness, Kevin; Giró-i-Nieto, Xavier; O'Connor, Noel E.; Smeaton, Alan F.
This paper explores the potential of brain-computer interfaces in segmenting objects from images. Our approach is centered around designing an effective method for displaying the image parts to the users such that they generate measurable brain reactions. When an image region, specifically a block of pixels, is displayed we estimate the probability of the block containing the object of interest using a score based on EEG activity. After several such blocks are displayed, the resulting probability map is binarized and combined with the GrabCut algorithm to segment the image into object and background regions. This study shows that BCI and simple EEG analysis are useful in locating object boundaries in images.
Keyword(s): Neuroscience; Signal processing; Artificial intelligence; Image processing
Publication Date:
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Mohedano, Eva, Healy, Graham ORCID: 0000-0001-6429-6339 <>, McGuinness, Kevin ORCID: 0000-0003-1336-6477 <>, Giró-i-Nieto, Xavier ORCID: 0000-0002-9935-5332 <>, O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <> and Smeaton, Alan F. ORCID: 0000-0003-1028-8389 <> (2014) Object segmentation in images using EEG signals. In: The 22nd ACM International Conference on Multimedia, 3-7 Nov 2014, Orlando, FL.. ISBN 978-1-4503-3063-3
Publisher(s): Association for Computing Machinery
File Format(s): application/pdf
Related Link(s):,
First Indexed: 2014-11-13 05:22:31 Last Updated: 2019-10-03 06:13:15